Robotics and Computer Vision Lab

Publications

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저 자 Gyeongmin Choe, Srinivasa G. Narasimhan, In So Kweon
학 회 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Spotlight]
Notes This research was supported by ONR Grant N00014-14-1-0595, NSF NRI grant IIS-1317749 and the Ministry of Trade, Industry & Energy and the Korea Evaluation Institute of Industrial Technology (KEIT) with the program number of 10060110.
논문일시(Year) 2016
논문일시(Month) 06
http://rcv.kaist.ac.kr/gmchoe/Project/NISAR/Near-Infrared (NIR) images of most materials exhibit less texture or albedo variations making them beneficial for vision tasks such as intrinsic image decomposition and structured light depth estimation. Understanding the reflectance properties (BRDF) of materials in the NIR wavelength range can be further useful for many photometric methods including shape from shading and inverse rendering. However, even with less albedo variation, many materials e.g. fabrics, leaves, etc. exhibit complex fine-scale surface detail making it hard to accurately estimate BRDF. In this paper, we present an approach to simultaneously estimate NIR BRDF and fine-scale surface details by imaging materials under different IR lighting and viewing directions. This is achieved by a novel iterative scheme that alternately estimates surface detail and NIR BRDF until convergence. Our setup does not require complicated gantries or calibration and we present the first NIR dataset of 100 materials including a variety of fabrics (knits, weaves, cotton, satin, leather), and organic (skin, leaves, jute, trunk, fur) and inorganic materials (plastic, concrete, carpet). The NIR BRDFs measured from material samples are used with a shape-from-shading algorithm to demonstrate fine-scale reconstruction of objects from a single NIR image.

List of Articles
625. Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation
Antyanta Bangunharcana, Jae Won Cho, Seokju Lee, In So Kweon, Kyung-Soo Kim, Soohyun Kim
International Conference on Intelligent Robots and Systems, IROS, 2021 2021 / 06
624. Deep Volumetric Depth Fusion for 3D Scene Reconstruction
Jaesung Choe, Sunghoon Im, Francois Rameau, Minjun Kang, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
623. Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation
Seokju Lee, Francois Rameau, Fei Pan, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
622. LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Inkyu Shin, Dong-Jin Kim, Jae Won Cho, Sanghyun Woo, Kwanyong Park, and In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2021 / 10
621. MS-UDA:Multi-Spectral Unsupervised Domain Adaptation for Thermal Image Semantic Segmentation
Yeong-Hyeon Kim, Ukcheol Shin, Jinsun Park, In So Kweon
IEEE Robotics and Automation Letters 2021 / 06
620. Depth Completion using Plane-Residual Representation
Byeong-Uk Lee, Kyunghyun Lee and In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2021 2021 / 06
619. Learning to Associate Every Segment for Video Panoptic Segmentation
Sanghyun Woo, Dahun Kim, Joon-Young Lee and In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2021 2021 / 06
618. Volumetric Propagation Network: Stereo-LiDAR Fusion for Long Range Depth Estimation
Jaesung Choe, Kyungdon Joo, Imtiaz Tooba, In So Kweon
IEEE Robotics and Automation Letters (RA-L) 2021 / 06
617. Stereo Object Matching Network
{Jaesung Choe, Kyungdon Joo}*, Francois Rameau, and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2021 / 06
616. Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective
{Chaoning Zhang, Philipp Benz}*, Adil Karjauv, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
615. Optical Flow Estimation from a Single Motion-blurred Image
Dawit Mureja Argaw, Junsik Kim, Francois Rameau, Jae Won Cho, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
614. Motion-blurred Video Interpolation and Extrapolation
Dawit Mureja Argaw, Junsik Kim, Francois Rameau, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
613. Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency
Seokju Lee, Sunghoon Im, Stephen Lin, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2021 / 02
612. ResNet or DenseNet? Introducing Dense Shortcuts to ResNet
Chaoning Zhang*, Philipp Benz*, Dawit Mureja Argaw, Seokju Lee, Junsik Kim, Francois Rameau, Jean-Charles Bazin, In So Kweon (*: equal contribution)
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 1
611. High-quality Frame Interpolation via Tridirectional Inference
Jinsoo Choi, Jaesik Park, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
610. Revisiting Batch Normalization for Improving Corruption Robustness
Philipp Benz*, Chaoning Zhang*, Adil Karjauv, and In So Kweon (*: equal contribution)
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
609. The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation
Myungchul Kim, Sanghyun Woo, Dahun Kim, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2021 / 01
608. UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging
Chaoning Zhang*, Philipp Benz*, Adil Karjauv*, Geng Sun, In-So Kweon (*: equal-contribution)
NeurIPS, 2020 2020 / 12
607. Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
KwanYong Park, Sanghyun Woo, Inkyu Shin, In So Kweon
NeurIPS, 2020 2020 / 12
606. An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search
Kyunghyun Lee, Byeong-Uk Lee, Ukcheol Shin, In So Kweon
NeurIPS, 2020 2020 / 12
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